P4-044: THE GCAD CLOUD-BASED WORKFLOW FOR PROCESSING WHOLE EXOME AND WHOLE GENOME DATA FROM THE ALZHEIMER'S DISEASE SEQUENCING PROJECT

2006 ◽  
Vol 14 (7S_Part_27) ◽  
pp. P1450-P1450
Author(s):  
Prabhakaran Gangadharan ◽  
Yuk Yee Leung ◽  
Otto Valladares ◽  
Yi-Fan Chou ◽  
Amanda B. Kuzma ◽  
...  
2020 ◽  
Vol 16 (S3) ◽  
Author(s):  
Gina M. Peloso ◽  
Yanbing Wang ◽  
Honghuang Lin ◽  
Chloé Sarnowski ◽  
Achilleas N. Pitsillides ◽  
...  

2020 ◽  
Author(s):  
Joseph S. Reddy ◽  
Mariet Allen ◽  
Xue Wang ◽  
Joanna M. Biernacka ◽  
Brandon J. Coombes ◽  
...  

AbstractBy analyzing whole-exome data from the Alzheimer’s disease sequencing project (ADSP), we identify a set of 4 genes that show highly significant association with Alzheimer’s disease (AD). These genes were identified within a human TREM2 co-expression network using a novel approach wherein prioritized polygenic score analyses were performed sequentially to identify significant polygenic components. Two of the 4 genes (TREM2, RIN3) have previously been linked to AD and two (ATP8B4, IL17RA) are novel. Like TREM2, the 2 novel AD genes are selectively expressed in human microglial cells. The most significant variants in ATP8B4 and IL17RA are non-synonymous variants with strong effects comparable to the APOE ε4 and ε2 alleles. These protein-altering variants will provide unique opportunities to further explore the biological role of microglial cells in AD and help inform future immune modulatory therapeutic development for AD.


2021 ◽  
Vol 12 ◽  
Author(s):  
Wan-Ping Lee ◽  
Albert A. Tucci ◽  
Mitchell Conery ◽  
Yuk Yee Leung ◽  
Amanda B. Kuzma ◽  
...  

Alzheimer’s Disease (AD) is a progressive neurologic disease and the most common form of dementia. While the causes of AD are not completely understood, genetics plays a key role in the etiology of AD, and thus finding genetic factors holds the potential to uncover novel AD mechanisms. For this study, we focus on copy number variation (CNV) detection and burden analysis. Leveraging whole-genome sequence (WGS) data released by Alzheimer’s Disease Sequencing Project (ADSP), we developed a scalable bioinformatics pipeline to identify CNVs. This pipeline was applied to 1,737 AD cases and 2,063 cognitively normal controls. As a result, we observed 237,306 and 42,767 deletions and duplications, respectively, with an average of 2,255 deletions and 1,820 duplications per subject. The burden tests show that Non-Hispanic-White cases on average have 16 more duplications than controls do (p-value 2e-6), and Hispanic cases have larger deletions than controls do (p-value 6.8e-5).


2019 ◽  
Vol 15 ◽  
pp. P623-P624
Author(s):  
Li-San Wang ◽  
Yuk Yee Leung ◽  
Otto Valladares ◽  
Yi-Fan Chou ◽  
Amanda B. Kuzma ◽  
...  

2017 ◽  
Vol 13 (7) ◽  
pp. P1490
Author(s):  
Xulong Wang ◽  
Christoph Preuss ◽  
Vivek Philip ◽  
Guruprasad Ananda ◽  
Casey Acklin ◽  
...  

2018 ◽  
Author(s):  
Adam C. Naj ◽  
Honghuang Lin ◽  
Badri N. Vardarajan ◽  
Simon White ◽  
Daniel Lancour ◽  
...  

AbstractThe Alzheimer’s Disease Sequencing Project (ADSP) performed whole genome sequencing (WGS) of 584 subjects from 111 multiplex families at three sequencing centers. Genotype calling of single nucleotide variants (SNVs) and insertion-deletion variants (indels) was performed centrally using GATK-HaplotypeCaller and Atlas V2. The ADSP Quality Control (QC) Working Group applied QC protocols to project-level variant call format files (VCFs) from each pipeline, and developed and implemented a novel protocol, termed “consensus calling,” to combine genotype calls from both pipelines into a single high-quality set. QC was applied to autosomal bi-allelic SNVs and indels, and included pipeline-recommended QC filters, variant-level QC, and sample-level QC. Low-quality variants or genotypes were excluded, and sample outliers were noted. Quality was assessed by examining Mendelian inconsistencies (MIs) among 67 parent-offspring pairs, and MIs were used to establish additional genotype-specific filters for GATK calls. After QC, 578 subjects remained. Pipeline-specific QC excluded ~12.0% of GATK and 14.5% of Atlas SNVs. Between pipelines, ~91% of SNV genotypes across all QCed variants were concordant; 4.23% and 4.56% of genotypes were exclusive to Atlas or GATK, respectively; the remaining ~0.01% of discordant genotypes were excluded. For indels, variant-level QC excluded ~36.8% of GATK and 35.3% of Atlas indels. Between pipelines, ~55.6% of indel genotypes were concordant; while 10.3% and 28.3% were exclusive to Atlas or GATK, respectively; and ~0.29% of discordant genotypes were. The final WGS consensus dataset contains 27,896,774 SNVs and 3,133,926 indels and is publicly available.AbbreviationsAD, Alzheimer’s disease; QC, Quality Control; LSSAC, Large-Scale Sequencing and Analysis Center; Broad, Broad Institute Genomics Service; Baylor, Baylor College of Medicine Human Genome Sequencing Center; WashU, Washington University-St. Louis McDonnell Genome Institute; WGS, whole genome sequencing; WES, whole exome sequencing; indel, insertion-deletion variants; VCF, variant control format; MI, Mendelian inconsistency; MC, Mendelian consistency; GWAS, genome-wide association study; VR, referent allele read depth; DP, overall read depth; MS, mapping score; GQ, genotype quality score; Ti/Tv, Transition/Transversion; CS, concordance code


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